After more than 150 years of ecological research, we still face challenges in understanding how ecosystems function, let alone how to predict future changes in light of climate change. Part of these challenges come from the scale on which we need to understand these dynamics as well as from the sheer complexity of these systems. There is a great deal of complexity in the natural world and scientific exploration has shown that in many times there are mathematical rules that can lead to such complexity. I aim at developing theoretical and empirical approaches to quantify the dynamics of ecosystems to find out what these rules are, to find out what processes play an important role in structuring communities, in both space and time. Combining approaches from multiple disciplines such as general ecology and evolution, information theory, physics and mathematics I aim at extending the ecological toolbox towards our capabilities of quantitatively studying these patterns. Specifically, I seek to further develop the connection between the field of information theory (maximum entropy), chaos theory and empirical evolutionary ecology to disentangle signals of quantitative selection and probability based processes in shaping ecological communities on both short and long timescales. In addition, my work aims at understanding patterns in species distribution using various principles from mathematics and physics, integrating these disciplines into accurate predictions of diversity and distribution.
In addition to reseach, I am involved in many academic courses. My teaching is primarily focused on undergraduate evolution and ecology, ranging from large-scale first year classes with over 400 students to classes of only 20-25 students involving much practical (field) work. My teaching consists of a broad spectrum of skills and experiences ranging from classical (but interactive) lectures, practical and theoretical assignments to actual fieldwork and experimental settings for the smaller classes. I endeavor to use multiple tools in my teaching, both classical and digital to accommodate not only efficient teaching but also education to motivate and stimulate curiosity among students and develop these tools where they are not yet available. In addition, I am the track coordinator of the study track Evolution and Biodiversity and the chairman of the educational advisory board of the Biology department.
Internationally, I am involved in two large-scale data networks: the Amazonian Tree Diversity Network, a collection of over 2100 hectares of forest inventory plots and the Nutrient Network, a global collaborative network of over 100 grassland sites involving experimental treatments, thereby simulating anthropogenic influences on community composition, productivity and functionality.
(theoretical) evolutionary ecology, biodiversity, community ecology, maximum entropy, chaos theory, Amazon, large-scale data analysis, complex statistics, R language, modeling